Hot Chips 2023 has concluded. Thank you to the speakers, attendees, sponsors, press, and volunteers!

Tutorials: Sunday, August 27, 2023

Time (PDT)	Title	Presenters
7:45AM-8:30AM	Breakfast/Registration
8:30AM-10:30AM	ML Inference Chair: Tom St. John
	ML Inference Overview	Micah Villmow, NVIDIA
	Quantization Methods for Efficient ML Inference	Amir Gholami, UC Berkeley
	ML Inference at the Edge	Felix Baum, Qualcomm
10:30AM-11:00AM	Coffee Break (1/2 hr)
11:00AM-12:15PM	ML Inference Chair: Tom St. John
	PyTorch 2.0	Elias Ellison, Meta
	Hardware Requirements for Exploiting Sparsity in ML Inference	Zhibin Xiao, Moffett AI
12:15PM-1:30PM	Lunch (1 hr 15 min)
1:30PM-3:30PM	Chiplets/UCI Chair: Debendra Das Sharma & Nathan Kalyansundharam
	UCIe Overview & Usage Models	Debendra Das Sharma, Intel & Nathan Kalyansundharam, AMD
	UCIe Protocol	Swadesh Choudhary, Intel & Marvin Denman, NVIDIA
3:30PM-4:00PM	Coffee Break (1/2 hr)
4:00PM-5:30PM	Chiplets/UCI Chair: Debendra Das Sharma & Nathan Kalyansundharam
	Electrical, Form Factor and Compliance	Anwar Kashem, AMD & Gerald Pasdast, Intel
	Software, Manageability & Security	Jérôme Glisse, Google & Sridhar Muthrasanallur, Intel
5:30PM-7:00PM	Reception

Conference Day 1: Monday, August 28, 2023

Time (PDT)	Title	Presenters
7:45AM-8:45AM	Breakfast/Registration
8:45AM-9:00AM	Opening Remarks
	General Chair Welcome	Gabriel Southern & Ron Diamant
	Progam Co-Chairs Welcome	Natalia Vassilieva & Heiner Litz
9:00AM-10:00AM	Keynote #1 Chair: Natalia Vassilieva
	Exciting Directions for ML Models and the Implications for Computing Hardware	Jeff Dean & Amin Vahdat, Google
10:00AM-11:00AM	Processing in Memory Chair: Jae W. Lee
	Memory-centric Computing with SK Hynix’s Domain-Specific Memory	Yongkee Kwon, SK Hynix
	Samsung AI-cluster system with HBM-PIM and CXL-based Processing-near-Memory for transformer-based LLMs	Jin Hyun Kim, Samsung
11:00AM-11:05AM	Sachs Memorial
	Sachs Memorial	Alan J Smith, UC Berkeley
11:05AM-11:30AM	Coffee Break
11:30AM-1:00PM	CPU 1 Chair: Pradeep K. Dubey
	ARM’s Neoverse V2 platform: leadership performance and power efficiency for next-generation cloud computing, ML and HPC workloads	Magnus Bruce, ARM
	AMD Next Generation “Zen 4” Core and 4th Gen AMD EPYCTM 9004 Server CPU	Kai Troester & Ravi Bhargava, AMD
	Ventana’s Veyron V1 Data Center-Class RISC-V Processor	Greg Favor, Ventana
1:00PM-2:15PM	Lunch (1 hr 15 min)
2:15PM-4:15PM	Platforms Chair: Mark D. Hill
	Architecting for Flexibility and Value with future Intel® Xeon® processors	Chris Gianos, Intel
	CSS-Genesis: Arm’s Neoverse N2 platform, delivered to partners as a fully verified, customizable compute sub-system	Anitha Kona, ARM
	Intel® Energy Efficiency Architecture	Efraim Rotem, Intel
	Caliptra: An Open-Source Root of Trust for Measurements	Bharat Pillilli, Microsoft
4:15PM-4:45PM	Coffee Break (1/2 hr)
4:45PM-6:15PM	CPU 2 Chair: Ralph Wittig
	Intel® Xeon® processors built on Efficient-core (E-Core): The Next Generation of High Performance, Energy-Efficient Computing	Don Soltis, Intel
	AMD Ryzen 7040 Series Mobile Processor	Mahesh Subramony & David Kramer, AMD
	Detailed Architecture Analysis and Key Features of SiFive’s latest high-performance out-of-order Vector Processor	Brad Burgess, SiFive
6:15PM-7:45PM	Reception

Conference Day 2: Tuesday, August 29, 2023

Time (PDT)	Title	Presenters
7:45AM-8:30AM	Breakfast/Registration
8:30AM-9:00AM	Poster Lighting Talks (2 minutes/poster) Chair: Priyanka Raina
	Poster Lighting Talks
9:00AM-10:00AM	Keynote #2 Chair: Heiner Litz
	Hardware for Deep Learning	Bill Dally, NVIDIA
10:00AM-11:00AM	ML-Training Chair: Dave Ditzel
	A Machine Learning Supercomputer With An Optically Reconfigurable Interconnect and Embeddings Support	Norman Jouppi & Andy Swing, Google
	Inside the Cerebras Wafer-Scale Cluster	Sean Lie, Cerebras
11:00AM-11:30AM	Coffee Break (1/2 hr)
11:30AM-1:00PM	Interconnects Chair: Yasuo Ishii
	NVIDIA’s Resource Transmutable Network Processing ASIC	Kevin Deierling, NVIDIA
	Hummingbird Low-Latency Computing Engine	Maurice Steinman, Lightelligence
	The First Direct Mesh-to-Mesh Photonic Fabric	Jason Howard, Intel
1:00PM-2:15PM	Lunch (1 hr 15 min)
2:15PM-4:15PM	ML-Inference Chair: Grant Ayers
	IBM NorthPole Neural Inference Machine	Dharmendra Modha, IBM
	Moffett Antoum: A Deep-Sparse AI Inference System-on-Chip for Vision and Large Language Models	Zhibin Xiao, Moffet AI
	Qualcomm® Hexagon™ NPU	Eric Mahurin, Qualcomm
	Supercharged AI inference on modern CPUs	Lawrence Spracklen & Subutai Ahmad, Numenta
4:15PM-4:45PM	Coffee Break (1/2 hr)
4:45PM-6:15PM	FPGAs & Cooling Chair: Forest Baskett
	AMD Next Generation FPGA Built From Chiplets	Dinesh Gaitonde, AMD
	Intel’s Agilex-9 Direct RF FPGAs with Integrated 64 GSPS Data Converters	Benjamin Esposito, Intel
	High Performance Cold Plates for Data Center Thermal Management via Electrochemical Additive Manufacturing (ECAM)	Ian Winfield, Fabric8Labs
6:15PM-6:30PM	Closing Remarks
	Closing Remarks	Gabriel Southern & Ron Diamant

Posters

(NOTE: Not all posters have videos)

Title	Authors & Affiliation
TrustForge: A Cryptographically Secure Enclave for Azure and AWS	Todd Austin, Valeria Bertacco and Alex Kisil; Agita Labs
An Open-Source 130-nm Fusion-Enabled Deconvolution Kernel Generator IC For Real-Time mmWave Radar Platform Motion Compensation	Nikhil Poole, Priyanka Raina and Amin Arbabian; Stanford University
A Scalable Multi-Chiplet Deep Learning Accelerator with Hub-Side 2.5D Heterogeneous Integration	Zhanhong Tan, Yifu Wu, Yannian Zhang, Haobing Shi, Wuke Zhang and Kaisheng Ma; Tsinghua University
PHEP: Paillier Homomorphic Encryption Processors for Privacy-Preserving Applications in Cloud Computing	Guiming Shi, Yi Li, Xueqiang Wang, Zhanhong Tan, Dapeng Cao, Jingwei Cai, Yuchen Wei, Zehua Li, Wuke Zhang, Yifu Wu, Wei Xu and Kaisheng Ma; Tsinghua University
HyperAccel LPU: Accelerating Hyperscale Models for Generative AI	Seungjae Moon, Junsoo Kim, Jung-Hoon Kim, Junseo Cha, Gyubin Choi, Seongmin Hong and Joo-Young Kim; HyperAccel / KAIST
An Abstract of SiMa.ai’s MLSoC Architecture	Srivi Dhruvanarayan; SiMa.ai
Shaheen: An Open, Secure, and Scalable RV64 SoC for Autonomous Nano-UAVs.	Luca Valente, Asif Hussain Chiralil Veeran, Mattia Sinigaglia, Yvan Tortorella, Alessandro Nadalini, Nils Wistoff, Bruno Sà, Angelo Garofalo, Rafail Psiakis, Mohammed Tolba, Ari Kulmala, Nimisha Limaye, Ozgur Sinanoglu, Sandro Pinto, Daniele Palossi, Luca Benini, Baker Mohammad and Davide Rossi; University of Bologna
A Heterogeneous SoC for Bluetooth LE in 28nm	Felicia Guo, Nayiri Krzysztofowicz, Alex Moreno, Jeffrey Ni, Daniel Lovell, Yufeng Chi, Kareem Ahmad, Sherwin Afshar, Josh Alexander, Dylan Brater, Cheng Cao, Daniel Fan, Ryan Lund, Jackson Paddock, Griffin Prechter, Troy Sheldon, Shreesha Sreedhara, Anson Tsai, Eric Wu, Kerry Yu, Daniel Fritchman, Aviral Pandey, Ali Niknejad, Kristofer Pister and Borivoje Nikolic; University of California Berkeley
Driving Compute Scale-out Performance with Optical I/O Chiplets in Advanced System-in-Package Platforms	Mark Wade, Chen Sun, Matt Sysak, Vladimir Stojanović, Pooya Tadayon, Ravi Mahajan and Babak Sabi; Ayar Labs
A Heterogeneous RISC-V SoC for ML Applications in Intel 16 Technology	Yufeng Chi, Franklin Huang, Raghav Gupta, Ella Schwarz, Jennifer Zhou, Reza Sajadiany, Animesh Agrawal, Max Banister, Michelle Boulos, Jason Chandran, Jessica Dowdall, Leena Elzeiny, Claire Gantan, Anthony Han, Roger Hsiao, Chadwick Leung, Edwin Lim, Jose Rodriguez, Tushar Sondhi, Mitchell Twu, Rongyi Wang, Mike Xiao, Ruohan Yan, Paul Kwon, Zhaokai Liu, Jerry Zhao, Bob Zhou, Ali Niknejad, Kristofer Pister and Borivoje Nikolić; University of California, Berkeley